Adjusting a dispersal parameter of dispersedly stored data

ABSTRACT

A method begins by a processing module storing data files utilizing a dispersed storage error coding function that includes a pillar width parameter and a decode threshold parameter. The method continues with the processing module determining whether to adjust the pillar width parameter based one or more memory performance characteristics. When the pillar width parameter is to be decreased, the method continues with the processing module identifying one or more pillars within a memory to delete to produce one or more identified pillars, identifying encoded data slices of one or more of the data files stored in the one or more identified pillars to produce identified encoded data slices, and deleting the identified encoded data slices.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 61/470,521,entitled “Flash Memory Utilization in a User Device of a DispersedStorage Network,” filed Apr. 1, 2011, pending, which is incorporatedherein by reference in its entirety and made part of the present U.S.Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computing systems and moreparticularly to data storage solutions within such computing systems.

2. Description of Related Art

Computers are known to communicate, process, and store data. Suchcomputers range from wireless smart phones to data centers that supportmillions of web searches, stock trades, or on-line purchases every day.In general, a computing system generates data and/or manipulates datafrom one form into another. For instance, an image sensor of thecomputing system generates raw picture data and, using an imagecompression program (e.g., JPEG, MPEG, etc.), the computing systemmanipulates the raw picture data into a standardized compressed image.

With continued advances in processing speed and communication speed,computers are capable of processing real time multimedia data forapplications ranging from simple voice communications to streaming highdefinition video. As such, general-purpose information appliances arereplacing purpose-built communications devices (e.g., a telephone). Forexample, smart phones can support telephony communications but they arealso capable of text messaging and accessing the internet to performfunctions including email, web browsing, remote applications access, andmedia communications (e.g., telephony voice, image transfer, musicfiles, video files, real time video streaming. etc.).

Each type of computer is constructed and operates in accordance with oneor more communication, processing, and storage standards. As a result ofstandardization and with advances in technology, more and moreinformation content is being converted into digital formats. Forexample, more digital cameras are now being sold than film cameras, thusproducing more digital pictures. As another example, web-basedprogramming is becoming an alternative to over the air televisionbroadcasts and/or cable broadcasts. As further examples, papers, books,video entertainment, home video, etc. are now being stored digitally,which increases the demand on the storage function of computers.

A typical computer storage system includes one or more memory devicesaligned with the needs of the various operational aspects of thecomputer's processing and communication functions. Generally, theimmediacy of access dictates what type of memory device is used. Forexample, random access memory (RAM) memory can be accessed in any randomorder with a constant response time, thus it is typically used for cachememory and main memory. By contrast, memory device technologies thatrequire physical movement such as magnetic disks, tapes, and opticaldiscs, have a variable response time as the physical movement can takelonger than the data transfer, thus they are typically used forsecondary memory (e.g., hard drive, backup memory, etc.).

A computer's storage system will be compliant with one or more computerstorage standards that include, but are not limited to, network filesystem (NFS), flash file system (FFS), disk file system (DFS), smallcomputer system interface (SCSI), internet small computer systeminterface (iSCSI), file transfer protocol (FTP), and web-baseddistributed authoring and versioning (WebDAV). These standards specifythe data storage format (e.g., files, data objects, data blocks,directories, etc.) and interfacing between the computer's processingfunction and its storage system, which is a primary function of thecomputer's memory controller.

Despite the standardization of the computer and its storage system,memory devices fail; especially commercial grade memory devices thatutilize technologies incorporating physical movement (e.g., a discdrive). For example, it is fairly common for a disc drive to routinelysuffer from bit level corruption and to completely fail after threeyears of use. One solution is to a higher-grade disc drive, which addssignificant cost to a computer.

Another solution is to utilize multiple levels of redundant disc drivesto replicate the data into two or more copies. One such redundant driveapproach is called redundant array of independent discs (RAID). In aRAID device, a RAID controller adds parity data to the original databefore storing it across the array. The parity data is calculated fromthe original data such that the failure of a disc will not result in theloss of the original data. For example, RAID 5 uses three discs toprotect data from the failure of a single disc. The parity data, andassociated redundancy overhead data, reduces the storage capacity ofthree independent discs by one third (e.g., n−1=capacity). RAID 6 canrecover from a loss of two discs and requires a minimum of four discswith a storage capacity of n−2.

While RAID addresses the memory device failure issue, it is not withoutits own failures issues that affect its effectiveness, efficiency andsecurity. For instance, as more discs are added to the array, theprobability of a disc failure increases, which increases the demand formaintenance. For example, when a disc fails, it needs to be manuallyreplaced before another disc fails and the data stored in the RAIDdevice is lost. To reduce the risk of data loss, data on a RAID deviceis typically copied on to one or more other RAID devices. While thisaddresses the loss of data issue, it raises a security issue sincemultiple copies of data are available, which increases the chances ofunauthorized access. Further, as the amount of data being stored grows,the overhead of RAID devices becomes a non-trivial efficiency issue.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a computingsystem in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an embodiment of a distributedstorage processing unit in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of a grid module inaccordance with the present invention;

FIG. 5 is a diagram of an example embodiment of error coded data slicecreation in accordance with the present invention;

FIG. 6 is a schematic block diagram of another embodiment of a computingsystem in accordance with the present invention;

FIG. 7A is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 7B is a flowchart illustrating an example of storing data inaccordance with the present invention;

FIG. 7C is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 7D is a flowchart illustrating an example of retrieving data inaccordance with the present invention;

FIG. 8A is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 8B is a flowchart illustrating an example of contracting datastorage in accordance with the present invention;

FIG. 9A is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 9B is a flowchart illustrating an example of expanding data storagein accordance with the present invention;

FIG. 10A is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 10B is a flowchart illustrating an example of accessing data inaccordance with the present invention;

FIG. 10C is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 10D is a flowchart illustrating an example of setting up adispersed storage in accordance with the present invention;

FIG. 11 is a flowchart illustrating an example of transferring data inaccordance with the present invention;

FIG. 12A is a flowchart illustrating an example of generating an encodeddata slice storage solicitation message in accordance with the presentinvention; and

FIG. 12B is a flowchart illustrating an example of processing an encodeddata slice storage solicitation message in accordance with the presentinvention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of a computing system 10 thatincludes one or more of a first type of user devices 12, one or more ofa second type of user devices 14, at least one distributed storage (DS)processing unit 16, at least one DS managing unit 18, at least onestorage integrity processing unit 20, and a distributed storage network(DSN) memory 22 coupled via a network 24. The network 24 may include oneor more wireless and/or wire lined communication systems; one or moreprivate intranet systems and/or public internet systems; and/or one ormore local area networks (LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of distributed storage (DS) units36 for storing data of the system. Each of the DS units 36 includes aprocessing module and memory and may be located at a geographicallydifferent site than the other DS units (e.g., one in Chicago, one inMilwaukee, etc.).

Each of the user devices 12-14, the DS processing unit 16, the DSmanaging unit 18, and the storage integrity processing unit 20 may be aportable computing device (e.g., a social networking device, a gamingdevice, a cell phone, a smart phone, a personal digital assistant, adigital music player, a digital video player, a laptop computer, ahandheld computer, a video game controller, and/or any other portabledevice that includes a computing core) and/or a fixed computing device(e.g., a personal computer, a computer server, a cable set-top box, asatellite receiver, a television set, a printer, a fax machine, homeentertainment equipment, a video game console, and/or any type of homeor office computing equipment). Such a portable or fixed computingdevice includes a computing core 26 and one or more interfaces 30, 32,and/or 33. An embodiment of the computing core 26 will be described withreference to FIG. 2.

With respect to the interfaces, each of the interfaces 30, 32, and 33includes software and/or hardware to support one or more communicationlinks via the network 24 indirectly and/or directly. For example,interfaces 30 support a communication link (wired, wireless, direct, viaa LAN, via the network 24, etc.) between the second type of user device14 and the DS processing unit 16. As another example, DSN interface 32supports a plurality of communication links via the network 24 betweenthe DSN memory 22 and the DS processing unit 16, the first type of userdevice 12, and/or the storage integrity processing unit 20. As yetanother example, interface 33 supports a communication link between theDS managing unit 18 and any one of the other devices and/or units 12,14, 16, 20, and/or 22 via the network 24.

In general and with respect to data storage, the system 10 supportsthree primary functions: distributed network data storage management,distributed data storage and retrieval, and data storage integrityverification. In accordance with these three primary functions, data canbe distributedly stored in a plurality of physically different locationsand subsequently retrieved in a reliable and secure manner regardless offailures of individual storage devices, failures of network equipment,the duration of storage, the amount of data being stored, attempts athacking the data, etc.

The DS managing unit 18 performs distributed network data storagemanagement functions, which include establishing distributed datastorage parameters, performing network operations, performing networkadministration, and/or performing network maintenance. The DS managingunit 18 establishes the distributed data storage parameters (e.g.,allocation of virtual DSN memory space, distributed storage parameters,security parameters, billing information, user profile information,etc.) for one or more of the user devices 12-14 (e.g., established forindividual devices, established for a user group of devices, establishedfor public access by the user devices, etc.). For example, the DSmanaging unit 18 coordinates the creation of a vault (e.g., a virtualmemory block) within the DSN memory 22 for a user device (for a group ofdevices, or for public access). The DS managing unit 18 also determinesthe distributed data storage parameters for the vault. In particular,the DS managing unit 18 determines a number of slices (e.g., the numberthat a data segment of a data file and/or data block is partitioned intofor distributed storage) and a read threshold value (e.g., the minimumnumber of slices required to reconstruct the data segment).

As another example, the DS managing module 18 creates and stores,locally or within the DSN memory 22, user profile information. The userprofile information includes one or more of authentication information,permissions, and/or the security parameters. The security parameters mayinclude one or more of encryption/decryption scheme, one or moreencryption keys, key generation scheme, and data encoding/decodingscheme.

As yet another example, the DS managing unit 18 creates billinginformation for a particular user, user group, vault access, publicvault access, etc. For instance, the DS managing unit 18 tracks thenumber of times user accesses a private vault and/or public vaults,which can be used to generate a per-access bill. In another instance,the DS managing unit 18 tracks the amount of data stored and/orretrieved by a user device and/or a user group, which can be used togenerate a per-data-amount bill.

The DS managing unit 18 also performs network operations, networkadministration, and/or network maintenance. As at least part ofperforming the network operations and/or administration, the DS managingunit 18 monitors performance of the devices and/or units of the system10 for potential failures, determines the devices and/or unit'sactivation status, determines the devices' and/or units' loading, andany other system level operation that affects the performance level ofthe system 10. For example, the DS managing unit 18 receives andaggregates network management alarms, alerts, errors, statusinformation, performance information, and messages from the devices12-14 and/or the units 16, 20, 22. For example, the DS managing unit 18receives a simple network management protocol (SNMP) message regardingthe status of the DS processing unit 16.

The DS managing unit 18 performs the network maintenance by identifyingequipment within the system 10 that needs replacing, upgrading,repairing, and/or expanding. For example, the DS managing unit 18determines that the DSN memory 22 needs more DS units 36 or that one ormore of the DS units 36 needs updating.

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has a data file 38 and/or data block 40 tostore in the DSN memory 22, it send the data file 38 and/or data block40 to the DS processing unit 16 via its interface 30. As will bedescribed in greater detail with reference to FIG. 2, the interface 30functions to mimic a conventional operating system (OS) file systeminterface (e.g., network file system (NFS), flash file system (FFS),disk file system (DFS), file transfer protocol (FTP), web-baseddistributed authoring and versioning (WebDAV), etc.) and/or a blockmemory interface (e.g., small computer system interface (SCSI), internetsmall computer system interface (iSCSI), etc.). In addition, theinterface 30 may attach a user identification code (ID) to the data file38 and/or data block 40.

The DS processing unit 16 receives the data file 38 and/or data block 40via its interface 30 and performs a distributed storage (DS) process 34thereon (e.g., an error coding dispersal storage function). The DSprocessing 34 begins by partitioning the data file 38 and/or data block40 into one or more data segments, which is represented as Y datasegments. For example, the DS processing 34 may partition the data file38 and/or data block 40 into a fixed byte size segment (e.g., 2¹ to2^(n) bytes, where n=>2) or a variable byte size (e.g., change byte sizefrom segment to segment, or from groups of segments to groups ofsegments, etc.).

For each of the Y data segments, the DS processing 34 error encodes(e.g., forward error correction (FEC), information dispersal algorithm,or error correction coding) and slices (or slices then error encodes)the data segment into a plurality of error coded (EC) data slices 42-48,which is represented as X slices per data segment. The number of slices(X) per segment, which corresponds to a number of pillars n, is set inaccordance with the distributed data storage parameters and the errorcoding scheme. For example, if a Reed-Solomon (or other FEC scheme) isused in an n/k system, then a data segment is divided into n slices,where k number of slices is needed to reconstruct the original data(i.e., k is the threshold). As a few specific examples, the n/k factormay be 5/3; 6/4; 8/6; 8/5; 16/10.

For each slice 42-48, the DS processing unit 16 creates a unique slicename and appends it to the corresponding slice 42-48. The slice nameincludes universal DSN memory addressing routing information (e.g.,virtual memory addresses in the DSN memory 22) and user-specificinformation (e.g., user ID, file name, data block identifier, etc.).

The DS processing unit 16 transmits the plurality of EC slices 42-48 toa plurality of DS units 36 of the DSN memory 22 via the DSN interface 32and the network 24. The DSN interface 32 formats each of the slices fortransmission via the network 24. For example, the DSN interface 32 mayutilize an internet protocol (e.g., TCP/IP, etc.) to packetize theslices 42-48 for transmission via the network 24.

The number of DS units 36 receiving the slices 42-48 is dependent on thedistributed data storage parameters established by the DS managing unit18. For example, the DS managing unit 18 may indicate that each slice isto be stored in a different DS unit 36. As another example, the DSmanaging unit 18 may indicate that like slice numbers of different datasegments are to be stored in the same DS unit 36. For example, the firstslice of each of the data segments is to be stored in a first DS unit36, the second slice of each of the data segments is to be stored in asecond DS unit 36, etc. In this manner, the data is encoded anddistributedly stored at physically diverse locations to improved datastorage integrity and security.

Each DS unit 36 that receives a slice 42-48 for storage translates thevirtual DSN memory address of the slice into a local physical addressfor storage. Accordingly, each DS unit 36 maintains a virtual tophysical memory mapping to assist in the storage and retrieval of data.

The first type of user device 12 performs a similar function to storedata in the DSN memory 22 with the exception that it includes the DSprocessing. As such, the device 12 encodes and slices the data fileand/or data block it has to store. The device then transmits the slices11 to the DSN memory via its DSN interface 32 and the network 24.

For a second type of user device 14 to retrieve a data file or datablock from memory, it issues a read command via its interface 30 to theDS processing unit 16. The DS processing unit 16 performs the DSprocessing 34 to identify the DS units 36 storing the slices of the datafile and/or data block based on the read command. The DS processing unit16 may also communicate with the DS managing unit 18 to verify that theuser device 14 is authorized to access the requested data.

Assuming that the user device is authorized to access the requesteddata, the DS processing unit 16 issues slice read commands to at least athreshold number of the DS units 36 storing the requested data (e.g., toat least 10 DS units for a 16/10 error coding scheme). Each of the DSunits 36 receiving the slice read command, verifies the command,accesses its virtual to physical memory mapping, retrieves the requestedslice, or slices, and transmits it to the DS processing unit 16.

Once the DS processing unit 16 has received a read threshold number ofslices for a data segment, it performs an error decoding function andde-slicing to reconstruct the data segment. When Y number of datasegments has been reconstructed, the DS processing unit 16 provides thedata file 38 and/or data block 40 to the user device 14. Note that thefirst type of user device 12 performs a similar process to retrieve adata file and/or data block.

The storage integrity processing unit 20 performs the third primaryfunction of data storage integrity verification. In general, the storageintegrity processing unit 20 periodically retrieves slices 45, and/orslice names, of a data file or data block of a user device to verifythat one or more slices have not been corrupted or lost (e.g., the DSunit failed). The retrieval process mimics the read process previouslydescribed.

If the storage integrity processing unit 20 determines that one or moreslices is corrupted or lost, it rebuilds the corrupted or lost slice(s)in accordance with the error coding scheme. The storage integrityprocessing unit 20 stores the rebuild slice, or slices, in theappropriate DS unit(s) 36 in a manner that mimics the write processpreviously described.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,at least one IO device interface module 62, a read only memory (ROM)basic input output system (BIOS) 64, and one or more memory interfacemodules. The memory interface module(s) includes one or more of auniversal serial bus (USB) interface module 66, a host bus adapter (HBA)interface module 68, a network interface module 70, a flash interfacemodule 72, a hard drive interface module 74, and a DSN interface module76. Note the DSN interface module 76 and/or the network interface module70 may function as the interface 30 of the user device 14 of FIG. 1.Further note that the IO device interface module 62 and/or the memoryinterface modules may be collectively or individually referred to as IOports.

FIG. 3 is a schematic block diagram of an embodiment of a dispersedstorage (DS) processing module 34 of user device 12 and/or of the DSprocessing unit 16. The DS processing module 34 includes a gatewaymodule 78, an access module 80, a grid module 82, and a storage module84. The DS processing module 34 may also include an interface 30 and theDSnet interface 32 or the interfaces 68 and/or 70 may be part of user 12or of the DS processing unit 14. The DS processing module 34 may furtherinclude a bypass/feedback path between the storage module 84 to thegateway module 78. Note that the modules 78-84 of the DS processingmodule 34 may be in a single unit or distributed across multiple units.

In an example of storing data, the gateway module 78 receives anincoming data object that includes a user ID field 86, an object namefield 88, and the data field 40 and may also receive correspondinginformation that includes a process identifier (e.g., an internalprocess/application ID), metadata, a file system directory, a blocknumber, a transaction message, a user device identity (ID), a dataobject identifier, a source name, and/or user information. The gatewaymodule 78 authenticates the user associated with the data object byverifying the user ID 86 with the managing unit 18 and/or anotherauthenticating unit.

When the user is authenticated, the gateway module 78 obtains userinformation from the management unit 18, the user device, and/or theother authenticating unit. The user information includes a vaultidentifier, operational parameters, and user attributes (e.g., userdata, billing information, etc.). A vault identifier identifies a vault,which is a virtual memory space that maps to a set of DS storage units36. For example, vault 1 (i.e., user 1's DSN memory space) includeseight DS storage units (X=8 wide) and vault 2 (i.e., user 2's DSN memoryspace) includes sixteen DS storage units (X=16 wide). The operationalparameters may include an error coding algorithm, the width n (number ofpillars X or slices per segment for this vault), a read threshold T, awrite threshold, an encryption algorithm, a slicing parameter, acompression algorithm, an integrity check method, caching settings,parallelism settings, and/or other parameters that may be used to accessthe DSN memory layer.

The gateway module 78 uses the user information to assign a source name35 to the data. For instance, the gateway module 78 determines thesource name 35 of the data object 40 based on the vault identifier andthe data object. For example, the source name may contain a fileidentifier (ID), a vault generation number, a reserved field, and avault identifier (ID). As another example, the gateway module 78 maygenerate the file ID based on a hash function of the data object 40.Note that the gateway module 78 may also perform message conversion,protocol conversion, electrical conversion, optical conversion, accesscontrol, user identification, user information retrieval, trafficmonitoring, statistics generation, configuration, management, and/orsource name determination.

The access module 80 receives the data object 40 and creates a series ofdata segments 1 through Y 90-92 in accordance with a data storageprotocol (e.g., file storage system, a block storage system, and/or anaggregated block storage system). The number of segments Y may be chosenor randomly assigned based on a selected segment size and the size ofthe data object. For example, if the number of segments is chosen to bea fixed number, then the size of the segments varies as a function ofthe size of the data object. For instance, if the data object is animage file of 4,194,304 eight bit bytes (e.g., 33,554,432 bits) and thenumber of segments Y=131,072, then each segment is 256 bits or 32 bytes.As another example, if segment sized is fixed, then the number ofsegments Y varies based on the size of data object. For instance, if thedata object is an image file of 4,194,304 bytes and the fixed size ofeach segment is 4,096 bytes, the then number of segments Y=1,024. Notethat each segment is associated with the same source name.

The grid module 82 receives the data segments and may manipulate (e.g.,compression, encryption, cyclic redundancy check (CRC), etc.) each ofthe data segments before performing an error coding function of theerror coding dispersal storage function to produce a pre-manipulateddata segment. After manipulating a data segment, if applicable, the gridmodule 82 error encodes (e.g., Reed-Solomon, Convolution encoding,Trellis encoding, etc.) the data segment or manipulated data segmentinto X error coded data slices 42-44.

The value X, or the number of pillars (e.g., X=16), is chosen as aparameter of the error coding dispersal storage function. Otherparameters of the error coding dispersal function include a readthreshold T, a write threshold W, etc. The read threshold (e.g., T=10,when X=16) corresponds to the minimum number of error-free error codeddata slices required to reconstruct the data segment. In other words,the DS processing module 34 can compensate for X−T (e.g., 16−10=6)missing error coded data slices per data segment. The write threshold Wcorresponds to a minimum number of DS storage units that acknowledgeproper storage of their respective data slices before the DS processingmodule indicates proper storage of the encoded data segment. Note thatthe write threshold is greater than or equal to the read threshold for agiven number of pillars (X).

For each data slice of a data segment, the grid module 82 generates aunique slice name 37 and attaches it thereto. The slice name 37 includesa universal routing information field and a vault specific field and maybe 48 bytes (e.g., 24 bytes for each of the universal routinginformation field and the vault specific field). As illustrated, theuniversal routing information field includes a slice index, a vault ID,a vault generation, and a reserved field. The slice index is based onthe pillar number and the vault ID and, as such, is unique for eachpillar (e.g., slices of the same pillar for the same vault for anysegment will share the same slice index). The vault specific fieldincludes a data name, which includes a file ID and a segment number(e.g., a sequential numbering of data segments 1-Y of a simple dataobject or a data block number).

Prior to outputting the error coded data slices of a data segment, thegrid module may perform post-slice manipulation on the slices. Ifenabled, the manipulation includes slice level compression, encryption,CRC, addressing, tagging, and/or other manipulation to improve theeffectiveness of the computing system.

When the error coded data slices of a data segment are ready to beoutputted, the grid module 82 determines which of the DS storage units36 will store the EC data slices based on a dispersed storage memorymapping associated with the user's vault and/or DS storage unitattributes. The DS storage unit attributes may include availability,self-selection, performance history, link speed, link latency,ownership, available DSN memory, domain, cost, a prioritization scheme,a centralized selection message from another source, a lookup table,data ownership, and/or any other factor to optimize the operation of thecomputing system. Note that the number of DS storage units 36 is equalto or greater than the number of pillars (e.g., X) so that no more thanone error coded data slice of the same data segment is stored on thesame DS storage unit 36. Further note that EC data slices of the samepillar number but of different segments (e.g., EC data slice 1 of datasegment 1 and EC data slice 1 of data segment 2) may be stored on thesame or different DS storage units 36.

The storage module 84 performs an integrity check on the outboundencoded data slices and, when successful, identifies a plurality of DSstorage units based on information provided by the grid module 82. Thestorage module 84 then outputs the encoded data slices 1 through X ofeach segment 1 through Y to the DS storage units 36. Each of the DSstorage units 36 stores its EC data slice(s) and maintains a localvirtual DSN address to physical location table to convert the virtualDSN address of the EC data slice(s) into physical storage addresses.

In an example of a read operation, the user device 12 and/or 14 sends aread request to the DS processing unit 14, which authenticates therequest. When the request is authentic, the DS processing unit 14 sendsa read message to each of the DS storage units 36 storing slices of thedata object being read. The slices are received via the DSnet interface32 and processed by the storage module 84, which performs a parity checkand provides the slices to the grid module 82 when the parity check wassuccessful. The grid module 82 decodes the slices in accordance with theerror coding dispersal storage function to reconstruct the data segment.The access module 80 reconstructs the data object from the data segmentsand the gateway module 78 formats the data object for transmission tothe user device.

FIG. 4 is a schematic block diagram of an embodiment of a grid module 82that includes a control unit 73, a pre-slice manipulator 75, an encoder77, a slicer 79, a post-slice manipulator 81, a pre-slice de-manipulator83, a decoder 85, a de-slicer 87, and/or a post-slice de-manipulator 89.Note that the control unit 73 may be partially or completely external tothe grid module 82. For example, the control unit 73 may be part of thecomputing core at a remote location, part of a user device, part of theDS managing unit 18, or distributed amongst one or more DS storageunits.

In an example of write operation, the pre-slice manipulator 75 receivesa data segment 90-92 and a write instruction from an authorized userdevice. The pre-slice manipulator 75 determines if pre-manipulation ofthe data segment 90-92 is required and, if so, what type. The pre-slicemanipulator 75 may make the determination independently or based oninstructions from the control unit 73, where the determination is basedon a computing system-wide predetermination, a table lookup, vaultparameters associated with the user identification, the type of data,security requirements, available DSN memory, performance requirements,and/or other metadata.

Once a positive determination is made, the pre-slice manipulator 75manipulates the data segment 90-92 in accordance with the type ofmanipulation. For example, the type of manipulation may be compression(e.g., Lempel-Ziv-Welch, Huffman, Golomb, fractal, wavelet, etc.),signatures (e.g., Digital Signature Algorithm (DSA), Elliptic Curve DSA,Secure Hash Algorithm, etc.), watermarking, tagging, encryption (e.g.,Data Encryption Standard, Advanced Encryption Standard, etc.), addingmetadata (e.g., time/date stamping, user information, file type, etc.),cyclic redundancy check (e.g., CRC32), and/or other data manipulationsto produce the pre-manipulated data segment.

The encoder 77 encodes the pre-manipulated data segment 92 using aforward error correction (FEC) encoder (and/or other type of erasurecoding and/or error coding) to produce an encoded data segment 94. Theencoder 77 determines which forward error correction algorithm to usebased on a predetermination associated with the user's vault, a timebased algorithm, user direction, DS managing unit direction, controlunit direction, as a function of the data type, as a function of thedata segment 92 metadata, and/or any other factor to determine algorithmtype. The forward error correction algorithm may be Golay,Multidimensional parity, Reed-Solomon, Hamming, Bose Ray ChauduriHocquenghem (BCH), Cauchy-Reed-Solomon, or any other FEC encoder. Notethat the encoder 77 may use a different encoding algorithm for each datasegment 92, the same encoding algorithm for the data segments 92 of adata object, or a combination thereof.

The encoded data segment 94 is of greater size than the data segment 92by the overhead rate of the encoding algorithm by a factor of X/T, whereX is the width or number of slices, and T is the read threshold. In thisregard, the corresponding decoding process can accommodate at most X−Tmissing EC data slices and still recreate the data segment 92. Forexample, if X=16 and T=10, then the data segment 92 will be recoverableas long as 10 or more EC data slices per segment are not corrupted.

The slicer 79 transforms the encoded data segment 94 into EC data slicesin accordance with the slicing parameter from the vault for this userand/or data segment 92. For example, if the slicing parameter is X=16,then the slicer 79 slices each encoded data segment 94 into 16 encodedslices.

The post-slice manipulator 81 performs, if enabled, post-manipulation onthe encoded slices to produce the EC data slices. If enabled, thepost-slice manipulator 81 determines the type of post-manipulation,which may be based on a computing system-wide predetermination,parameters in the vault for this user, a table lookup, the useridentification, the type of data, security requirements, available DSNmemory, performance requirements, control unit directed, and/or othermetadata. Note that the type of post-slice manipulation may includeslice level compression, signatures, encryption, CRC, addressing,watermarking, tagging, adding metadata, and/or other manipulation toimprove the effectiveness of the computing system.

In an example of a read operation, the post-slice de-manipulator 89receives at least a read threshold number of EC data slices and performsthe inverse function of the post-slice manipulator 81 to produce aplurality of encoded slices. The de-slicer 87 de-slices the encodedslices to produce an encoded data segment 94. The decoder 85 performsthe inverse function of the encoder 77 to recapture the data segment90-92. The pre-slice de-manipulator 83 performs the inverse function ofthe pre-slice manipulator 75 to recapture the data segment 90-92.

FIG. 5 is a diagram of an example of slicing an encoded data segment 94by the slicer 79. In this example, the encoded data segment 94 includesthirty-two bits, but may include more or less bits. The slicer 79disperses the bits of the encoded data segment 94 across the EC dataslices in a pattern as shown. As such, each EC data slice does notinclude consecutive bits of the data segment 94 reducing the impact ofconsecutive bit failures on data recovery. For example, if EC data slice2 (which includes bits 1, 5, 9, 13, 17, 25, and 29) is unavailable(e.g., lost, inaccessible, or corrupted), the data segment can bereconstructed from the other EC data slices (e.g., 1, 3 and 4 for a readthreshold of 3 and a width of 4).

FIG. 6 is a schematic block diagram of another embodiment of a computingsystem that includes one or more user devices 12, a dispersed storage(DS) processing unit 16, a network 24, and a dispersed storage network(DSN) memory 22. The user device 12 may include one or more of acomputing core 26, an interface 32, a Flash memory 102, and a magneticdrive memory 104. The computing core 26 includes a DS processing 34. TheDS memory 22 includes a plurality of DS units 36. The DS unit 36includes one or more of the computing core 26, the interface 32, theFlash memory 102, and the magnetic drive memory 104.

The Flash memory 102 provides a first memory type and may be implementedutilizing non-volatile electrically erasable programmable read-onlymemory (EEPROM). An alternative non-volatile solid-state storagetechnology including one or more of static random access memory (SRAM)and dynamic random access memory (DRAM) may be utilized as a substitutefor the Flash memory 102. The magnetic drive memory 104 provides asecond memory type and may be implemented utilizing a non-volatilerandom access memory device that includes rotating rigid platters spunby a motor, wherein the rotating rigid platters serve to magneticallystore data that is written and read utilizing a read/write head thatfloats above the platters. Such a first memory device type and a secondmemory device type provide storage of data in accordance with memorystorage characteristics. For example, the first memory device typeprovides faster access via lower access latency when implemented withFlash memory technology as compared to the second memory device typewhen implemented with magnetic drive memory technology. As anotherexample, the second memory device type provides lower-cost storage on anormalized basis when implemented with the magnetic drive memorytechnology as compared to the first memory device type when implementedwith the flash memory technology.

The DS processing 34 of the user device 12 of the one or more userdevices 12 generates encoded data slices and facilitates storing theencoded data slices in one or more memories of the computing system.Alternatively, a DS processing unit 34 of the DS processing unit 16generates encoded data slices and facilitates storing the encoded dataslices in the one or more memories of the computing system. The memoriesof the computing system includes Flash memory 102 of each user device 12of the one or more user devices 12, magnetic drive memory 104 of eachuser device 12 of the one or more user devices 12, Flash memory 102 ofeach DS unit 36 of the plurality of DS units 36, and magnetic drivememory 104 of each DS unit 36 of the plurality of the DSN memory 22.

The DS processing 34 facilitates the storing of the encoded data slicesin the one or more memories of the computing system by selecting one ormore storage locations based on a storage requirement. The storagerequirement includes one or more of a security requirement, aperformance requirement, a reliability requirement, a predetermination,a cost requirement, a memory availability indicator, and a memoryavailability requirement. For example, the DS processing 34 selects alocal Flash memory 102 of an associated user device 12 when theperformance requirement includes a very low retrieval access latencyrequirement. As another example, the DS processing 34 selects a magneticdrive memory 104 of a DS unit 36 when the cost requirement indicates avery low cost requirement and when the reliability requirement indicatesa very high required reliability level. As yet another example, the DSprocessing 34 selects a set of Flash memories associated with a set ofother user devices 12 when a set of memory availability indicatorsassociated with the set of other user devices 12 compares favorably tothe memory availability requirement.

In an example of operation, a DS processing 34 of a first user device 12dispersed storage error encodes data to produce a plurality of sets ofencoded data slices. The DS processing 34 selects a set of Flashmemories associated with a set of other user devices 12 of the one ormore user devices 12. The DS processing 34 stores a decode thresholdnumber (e.g., k) of encoded data slices of a set of the plurality ofsets of encoded data slices in a local flash memory associated with thefirst user device 12. The DS processing 34 outputs other encoded dataslices of the set of the plurality of sets of encoded data slices to theset of other user devices 12 via the interface 32 and the network 24 forstorage therein.

In another example of operation, the DS processing 34 of the first userdevice 12 dispersed storage error encodes data to produce the pluralityof sets of encoded data slices. The DS processing 34 selects a set ofmagnetic drive memories associated with a set of DS units 36 of theplurality of DS units 36. The DS processing 34 stores the decodethreshold number (e.g., k) of encoded data slices of the set of theplurality of sets of encoded data slices in the local flash memoryassociated with the first user device 12. The DS processing 34 outputsother encoded data slices of the set of the plurality of sets of encodeddata slices to the set of DS units 36 via the interface 32 of the firstuser device 12, the network 24, the interface 32 of each DS unit 36 ofthe set of DS units 36, and each computing core 26 of the set of DSunits 36 for storage in a set of magnetic drive memories of the set ofDS units 36.

Alternatively, the DS processing 34 outputs the other encoded dataslices of a set of the plurality of sets of encoded data slices via theinterface 32 of the first user device 12 and the network 24 to the DSprocessing unit 16. Next, the DS processing unit 16 dispersed storageerror encodes each encoded data slice of the other encoded data slicesto produce a plurality of groups of at least one set of encoded datasub-slice corresponding to each encoded data slice of the other encodeddata slices. The DS processing unit 16 sends the plurality of groups ofat least one encoded data sub-slice via the network 24 to a set of DSunits 36 for storage therein. The method of operation is discussed ingreater detail with reference to FIGS. 7A-12B.

FIG. 7A is a schematic block diagram of another embodiment of acomputing system that includes a computing device 110, a dispersedstorage (DS) processing unit 16, and a dispersed storage network (DSN)memory 22. The DSN memory 22 includes one or more of a secondarymagnetic drive memory, a computing device memory, a user device memory,and at least one set of DS units. The computing device 110 includes a DSmodule 112 and a local memory 114. The local memory 114 may include oneor more memory devices, wherein each memory device includes one or moreof a flash memory 102, a magnetic drive memory 104, a primary magneticdrive memory, a computing device memory, a local user device memory, asolid-state memory, and an optical memory. Alternatively, the localmemory 114 may include memory associated with two or more computingdevices 110. The DS module 112 includes an encode data module 116, astore slices module 118, and an output remaining slices module 120.

The encode data module 116, when operable within a computing device,causes the computing device 110 to encode data 122 utilizing a dispersedstorage error coding function to produce a set of encoded data slices124, wherein the dispersed storage error coding function includes adecode threshold parameter and a pillar width parameter. The encodingmay further include receiving a data storage request, wherein therequest includes a storage requirement including one or more ofreliability, memory utilization, access latency, and security. Theencode data module 116 further functions to encode the data 122 byestablishing the decode threshold parameter and the pillar widthparameter based on one or more of physical characteristics of the localmemory and a local memory performance characteristic. The local memoryperformance characteristic includes one or more of memory utilization,data retrieval reliability, and data retrieval latency. The local memoryphysical characteristic includes one or more of a type of memory deviceand a number of memory devices included in the local memory 114. Forexample, the encode data module 116 establishes the decode thresholdparameter as 10 when the local memory 114 includes 10 memory devices. Asanother example, the encode data module 116 establishes the decodethreshold parameter as 5 and the pillar width parameter as 21 when thelocal memory 114 includes three memory devices and a local memoryperformance characteristic indicates a below average data retrievalreliability level.

The store slices module 118, when operable within the computing device,causes the computing device to store a number of encoded data slices 126of the set of encoded data slices 124 in the local memory 114, whereinthe number is based on the decode threshold parameter and is less thanthe pillar width parameter. The storing may include selecting the numberof encoded data slices 126 and writing each of the number of encodeddata slices 126 to the local memory 114. The store slices module 118,when operable within the computing device 110, further causes thecomputing device 110 to determine the number of encoded data slices 126by at least one of performing a mathematical function on the decodethreshold parameter and performing a second mathematical function basedon at least one of physical structure of the local memory andperformance characteristics of the local memory 114. For example, thestore slices module 118 determines the number of encoded data slices 126to be the decode threshold parameter when a physical structure of thelocal memory indicates that more than a decode threshold parameternumber of memory devices are available. As another example, the storeslices module 118 determines the number of encoded data slices 126 to bethe decode threshold parameter minus two when a performancecharacteristic of the local memory 114 indicates below averageperformance. As yet another example, the store slices module 118determines the number of encoded data slices 126 to be the decodethreshold parameter plus three when a physical structure of the localmemory 114 indicates that less than a decode threshold parameter numberof memory devices are available.

The encode data module 116, when operable within the computing device110, further causes the computing device 110 to encode the datautilizing the dispersed storage error coding function to produce aplurality of sets of encoded data slices, which includes the set ofencoded data slices. The store slices module 118, when operable withinthe computing device 110, further causes the computing device 110 todetermine, in accordance with a set storage protocol, the number ofencoded data slices of one or more sets of the plurality of sets ofencoded data slices. For example, the store slices module 118 determinesa common number of encoded data slices for each set of the plurality ofsets of encoded data slices when a set storage protocol indicates toutilize a common number. As another example, the store slices module 118determines a unique number of encoded data slices for each set of theplurality of sets of encoded data slices when a set storage protocolindicates to utilize a unique number for each set of encoded dataslices.

The store slices module 118 further functions to store the number ofencoded data slices 126 by selecting the number of encoded data slices126 from the set of encoded data slices 124 based on the dispersedstorage error coding function and issuing a number of write requests tothe local memory 114 for the number of encoded data slices 126. Forexample, the store slices module 118 selects the number of encoded dataslices 126 aligned with subsequent decoding of the decode thresholdparameter number of encoded data slices to improve recovery latencytime. For instance, the store slices module 118 selects the number ofencoded data slices associated with a first decode threshold parameternumber of pillars when a unity matrix is used within a generator matrixof the dispersed storage error coding function.

The output remaining slices module 120, when operable within thecomputing device 110, causes the computing device 110 to outputremaining encoded data slices 128 of the set of encoded data slices 124to the DSN memory 22. The outputting may include selecting the remainingencoded data slices 128 (e.g., pillar width-number) and sending theremaining encoded data slices 128 to the DSN memory 22. The outputremaining slices module 120 further functions to output the remainingencoded data slices 128 by sending the remaining encoded data slices 128to the DS processing unit 16; or (e.g., the DS processing unit 16directly stores slices or encodes new slices for storage in the DSNmemory 22) sending the data 122 and the number to the DS processing unit16, wherein the DS processing unit 16 encodes the data 122 utilizing thedispersed storage error coding function to produce another set ofencoded data slices, identifies the remaining encoded data slices 128from the other set of encoded data slices based on the number and the aset by set basis, for the plurality, or for groupings of the plurality,and outputs the remaining encoded data slices 128 to the DSN memory 22;and updating an encoded data slice mapping. The updating of the encodeddata slice mapping includes listing identities of one or more of theremaining encoded data slices 128, a DSN source name received from theDS processing unit 16, and a corresponding identity of the DS processingunit 16.

The outputting remaining encoded data slices 128 further includes one ormore of selecting a memory of the DSN memory 22 based on one or more DSNmemory performance characteristics (e.g., DSN memory utilization, DSNmemory data retrieval reliability, DSN memory data retrieval latency;selecting further includes selecting based on at least one of a securityrequirement, a predetermination, and a message), sending a write encodeddata slice request to the at least one memory for each encoded dataslice of the remaining encoded data slices 128, wherein each writeencoded data slice request includes a corresponding encoded data sliceof the remaining encoded data slices 128, and updating an encoded dataslice mapping. (e.g., list identities of the remaining encoded dataslices 128 and corresponding identities of the selected at least onememory)

FIG. 7B is a flowchart illustrating an example of storing data. Themethod begins at step 130 where a processing module (e.g., of acomputing device) encodes data utilizing a dispersed storage errorcoding function to produce a set of encoded data slices, wherein thedispersed storage error coding function includes a decode thresholdparameter and a pillar width parameter. The encoding the data furtherincludes establishing the decode threshold parameter and the pillarwidth parameter based on one or more of physical characteristics of thelocal memory and a local memory performance characteristic.Alternatively, or in addition to, the processing module encodes the datautilizing the dispersed storage error coding function to produce aplurality of sets of encoded data slices, which includes the set ofencoded data slices.

The method continues at step 132 where the processing module determinesthe number of encoded data slices by at least one of performing amathematical function on the decode threshold parameter and performing asecond mathematical function based on at least one of physical structureof the local memory and performance characteristics of the local memory.Alternatively, or in addition to, the processing module determines, inaccordance with a set storage protocol, the number of encoded dataslices of one or more sets of the plurality of sets of encoded dataslices when the data is encoded to produce the plurality of sets ofencoded data slices.

The method continues at step 134 where the processing module stores anumber of encoded data slices of the set of encoded data slices in alocal memory, wherein the number is based on the decode thresholdparameter and is less than the pillar width parameter. The storing thenumber of encoded data slices further includes selecting the number ofencoded data slices from the set of encoded data slices based on thedispersed storage error coding function and issuing a number of writerequests to the local memory for the number of encoded data slices.

The method continues at step 136 where the processing module outputsremaining encoded data slices of the set of encoded data slices todispersed storage network (DSN) memory. The outputting remaining encodeddata slices further includes sending the remaining encoded data slicesto a dispersed storage processing unit or sending the data and thenumber to a dispersed storage (DS) processing unit, wherein the DSprocessing unit encodes the data utilizing the dispersed storage errorcoding function to produce another set of encoded data slices,identifying the remaining encoded data slices from the other set ofencoded data slices based on the number and the a set by set basis, forthe plurality, or for groupings of the plurality and outputting theremaining encoded data slices to the DSN memory; and updating an encodeddata slice mapping. The outputting remaining encoded data slices furtherincludes one or more of selecting a memory of the DSN memory based onone or more DSN memory performance characteristics, sending a writeencoded data slice request to the at least one memory for each encodeddata slice of the remaining encoded data slices, wherein each writeencoded data slice request includes a corresponding encoded data sliceof the remaining encoded data slices, and updating an encoded data slicemapping.

FIG. 7C is a schematic block diagram of another embodiment of acomputing system that includes a computing device 140, a dispersedstorage (DS) processing unit 16, and a dispersed storage network (DSN)memory 22. The DSN memory 22 includes one or more of a secondarymagnetic drive memory, a computing device memory, a user device memory,and at least one set of DS units. The computing device 140 includes a DSmodule 142 and a local memory 114. The local memory 114 may include oneor more memory devices, wherein each memory device includes one or moreof a flash memory 102, a magnetic drive memory 104, a primary magneticdrive memory, a computing device memory, a local user device memory, asolid-state memory, and an optical memory. Alternatively, the localmemory 114 may include memory associated with two or more computingdevices 140. The DS module 142 includes a receive request module 144, anissue local requests module 146, receive local slices module 148, anissue DSN requests module 150, and a decode slices module 152. Thereceive request module 144, when operable within the computing device140, causes the computing device 140 to receive a retrieval request 154for data 122, wherein the data 122 is encoded utilizing a dispersedstorage error coding function to produce a set of encoded data slices124, wherein a number of encoded data slices 126 of the set of encodeddata slices 124 are stored in the local memory 114 and remaining encodeddata slices 128 of the set of encoded data slices 124 are stored in theDSN memory 22.

The issue local requests module 146, when operable within the computingdevice 140, causes the computing device 140 to issue a number of dataread requests 156 to the local memory 114 for retrieval of the number ofencoded data slices 126. The issue local requests module 146 functionsto issue the number of data read requests 156 by determining the numberof data read requests 156 by at least one of performing a number look upoperation (e.g., from a previous storage sequence), performing amathematical function on a decode threshold parameter, and performing asecond mathematical function based on at least one of physical structureof the local memory and performance characteristics of the local memory,wherein the dispersed storage error coding function includes a decodethreshold parameter and a pillar width parameter.

The receive local slices module 148, when operable within the computingdevice 140, causes the computing device 140 to determine whether adecode threshold number of encoded data slices have been received fromthe local memory 114. The receive local slices module 148 functions todetermine whether a decode threshold number of encoded data slices havebeen received by one of determining that the decode threshold number ofencoded data slices have not been received when the number of data readrequests 156 is less than a decode threshold parameter and when thenumber of data read requests 156 is greater than or equal to the decodethreshold parameter decode threshold, determining whether the decodethreshold number of encoded data slices have been received within agiven time frame.

When the decode threshold number of encoded data slices have not beenreceived (e.g., within a time period) from the local memory 114, theissue DSN requests module 150, when operable within the computing device140, causes the computing device 140 to issue one or more data readrequests 158 to the DSN memory 22 (e.g., directly to the DSN memory 22or via the DS processing unit 16) for retrieving one or more of theremaining encoded data slices 128. The issue DSN requests module 150functions to issue the one or more data read requests 158 to the DSNmemory 22 by selecting the one or more of the remaining encoded dataslices 128 based on one or more of an encoded data slice mappingretrieval, a query, a message, and the data retrieval request. Inaddition, the issue DSN requests module 150 sends the one or more dataread requests 158 to the DSN memory 22. When the decode threshold numberof encoded data slices have been received (e.g., directly from the DSNmemory 22 to the decode slices module 152 or via the DS processing unit16), the decode slices module 152, when operable within the computingdevice 140, causes the computing device 140 to decode the decodethreshold number of encoded data slices using the dispersed storageerror coding function to reproduce the data 122.

FIG. 7D is a flowchart illustrating an example of retrieving data. Themethod begins at step 160 where a processing module (e.g., of acomputing device) receives a retrieval request for data, wherein thedata is encoded utilizing a dispersed storage error coding function toproduce a set of encoded data slices, wherein a number of encoded dataslices of the set of encoded data slices are stored in a local memoryand remaining encoded data slices of the set of encoded data slices arestored in dispersed storage network (DSN) memory.

The method continues at step 162 where the processing module issues anumber of data read requests to the local memory for retrieval of thenumber of encoded data slices. The issuing the number of data readrequests includes determining the number of data read requests by atleast one of performing a number look up operation, performing amathematical function on a decode threshold parameter, and performing asecond mathematical function based on at least one of physical structureof the local memory and performance characteristics of the local memory,wherein the dispersed storage error coding function includes a decodethreshold parameter and a pillar width parameter.

The method continues at step 164 where the processing module determineswhether a decode threshold number of encoded data slices have beenreceived from the local memory. The determining whether a decodethreshold number of encoded data slices have been received includes oneof determining that the decode threshold number of encoded data sliceshave not been received when the number of data read requests is lessthan a decode threshold parameter and when the number of data readrequests is greater than or equal to the decode threshold parameterdecode threshold, determining whether the decode threshold number ofencoded data slices have been received within a given time frame. Themethod branches to step 168 when the processing module determines thatthe decode threshold number of encoded data slices have been received.The method continues to step 166 when the processing module determinesthat the decode threshold number of encoded data slices have not beenreceived (e.g., within a given time period).

The method continues at step 166 where the processing module issues oneor more data read requests to the DSN memory for retrieving one or moreof the remaining encoded data slices. The issuing the one or more dataread requests to the DSN memory includes selecting the one or more ofthe remaining encoded data slices based on one or more of an encodeddata slice mapping retrieval, a query, a message, and the data retrievalrequest. When the decode threshold number of encoded data slices havebeen received, the method continues at step 168 where the processingmodule decodes the decode threshold number of encoded data slices usingthe dispersed storage error coding function to reproduce the data.

FIG. 8A is a schematic block diagram of another embodiment of acomputing system that includes a computing device 170 and a dispersedstorage network (DSN) memory 22. The DSN memory 22 includes one or moreof a secondary magnetic drive memory, a computing device memory, a userdevice memory, and at least one set of DS units. The computing device170 includes a DS module 172 and a local memory 174. The local memory174 may include one or more memory devices, wherein each memory deviceincludes one or more of a flash memory 102, a magnetic drive memory 104,a primary magnetic drive memory, a computing device memory, a local userdevice memory, a solid-state memory, and an optical memory. The DSmodule 172 includes a store data files module 176, a determine pillaradjustment module 178, and a contract pillars module 180.

The store data files module 176, when operable within the computingdevice 170, causes the computing device 170 to store data files 182utilizing a dispersed storage error coding function, wherein a data fileof the data files is encoded using the dispersed storage error codingfunction to produce a plurality of sets of encoded data slices 184,wherein the plurality of sets of encoded data slices 184 is stored inmemory, and wherein the dispersed storage error coding function includesa pillar width parameter and a decode threshold parameter, where thepillar width parameter is at least 1.8 times the decode thresholdparameter (e.g., a pillar width parameter of 100 and a decode thresholdparameter of 10). The memory includes one or more of the local memory174 and the DSN memory 22. The store data files module 176, whenoperable within the computing device 170, further causes the computingdevice 170 to encode a subsequent data file utilizing a decreased pillarwidth parameter 186 (e.g., 60), the decode threshold parameter, and thedispersed storage error coding function to produce a subsequentplurality of sets of encoded data slices and store the subsequentplurality of sets of encoded data slices in the memory.

The determine pillar adjustment module 178, when operable within thecomputing device 170, causes the computing device 170 to determinewhether to adjust the pillar width parameter based one or more memoryperformance characteristics 188 (e.g., availability and/or reliability).The determine pillar adjustment module 178 functions to determine todecrease the pillar width parameter by determining a memory utilizationindicator associated with the memory (e.g., includes obtaining thememory utilization indicator based on one or more of a lookup, a query,a test, and receiving a message), determining a memory reliabilityindicator associated with the memory, and when the memory utilizationindicator is unfavorable and the memory reliability indicator isfavorable, indicating a decrease of the pillar width parameter. Thememory utilization indicator includes one or more of an amount ofavailable memory, an amount of utilized memory, available memorypercentage of memory capacity, and utilized memory percentage of memorycapacity. The memory reliability indicator includes one or more of anaccess latency level of the local memory, a rebuilding frequencyindicator, and a data retrieval reliability level of the memory. Forexample, the determine pillar adjustment module 178 decreases the pillarwidth parameter from 100 to 60 when an amount of utilized memory isgreater than a memory threshold and a data retrieval reliability levelcompares favorably to a reliability threshold.

When the pillar width parameter is to be decreased, the contract pillarsmodule 180, when operable within the computing device 170, causes thecomputing device 170 to identify one or more pillars within the memoryto delete to produce one or more identified pillars (e.g., and producethe decreased pillar width parameter 186), identify encoded data slicesof one or more of the data files stored in the one or more identifiedpillars to produce identified encoded data slices, and delete theidentified encoded data slices (e.g., by sending delete encoded dataslice requests 190 to the DSN memory 22 with regards to the identifiedencoded data slices). The contract pillars module 180 functions toidentify the one or more pillars within the memory to delete bydetermining an amount of memory space to reclaim based on at least oneof a memory utilization indicator and a memory reliability indicator,identifying one or more of the data files based on data file criteria(e.g., user identifier, minimum file size, a file priority indicator),and determining a number of pillars to be deleted based on the amount ofmemory space to reclaim and the identified one or more of the datafiles. For example, the contract pillars module 180 identifies pillars61-100 to delete corresponding to 50 data files associated with a lowerthan average file priority indicator value to reclaim 100 GB of memoryspace.

The contract pillars module 180 functions to delete the identifiedencoded data slices by reclaiming memory space of the deleted encodeddata slices and updating pillar mapping of the memory in accordance withthe decreasing of the pillar width parameter and the reclaimed memoryspace (e.g., reassign slice name ranges per memory). The contractpillars module 180 functions to identify the encoded data slices byidentifying the one or more of the data files (e.g., based on filepriority) and for each of the one or more identified data filesdetermining which of the encoded data slices of a respective pluralityof sets of encoded data slices are stored in the one or more identifiedpillars to produce data file specific encoded data slices, wherein theidentified encoded data slices includes the data file specific encodeddata slices for each of the one or more identified data files.

FIG. 8B is a flowchart illustrating an example of contracting datastorage. The method begins at step 200 where a processing module (e.g.,of a computing device) stores data files utilizing a dispersed storageerror coding function, wherein a data file of the data files is encodedusing the dispersed storage error coding function to produce a pluralityof sets of encoded data slices, wherein the plurality of sets of encodeddata slices is stored in memory, and wherein the dispersed storage errorcoding function includes a pillar width parameter and a decode thresholdparameter, where the pillar width parameter is at least 1.8 times thedecode threshold parameter. The memory includes one or more of a localmemory and a dispersed storage network (DSN) memory. Alternatively, orin addition to, processing module encodes a subsequent data fileutilizing the decreased pillar width parameter, the decode thresholdparameter, and the dispersed storage error coding function to produce asubsequent plurality of sets of encoded data slices and stores thesubsequent plurality of sets of encoded data slices in the memory.

The method continues at step 202 where the processing module determineswhether to adjust the pillar width parameter based on one or more memoryperformance characteristics. The determining to decrease the pillarwidth parameter includes determining a memory utilization indicatorassociated with the memory, determining a memory reliability indicatorassociated with the memory, and when the memory utilization indicator isunfavorable and the memory reliability indicator is favorable,indicating a decrease of the pillar width parameter.

When the pillar width parameter is to be decreased, the method continuesat step 204 where the processing module identifies one or more pillarswithin the memory to delete to produce one or more identified pillars.The identifying one or more pillars within the memory to delete includesdetermining an amount of memory space to reclaim based on at least oneof a memory utilization indicator and a memory reliability indicator,identifying one or more of the data files based on data file criteria,and determining a number of pillars to be deleted based on the amount ofmemory space to reclaim and the identified one or more of the datafiles.

The method continues at step 206 where the processing module identifiesencoded data slices of one or more of the data files stored in the oneor more identified pillars to produce identified encoded data slices.The identifying encoded data slices includes identifying the one or moreof the data files and for each of the one or more identified data files,determining which of the encoded data slices of a respective pluralityof sets of encoded data slices are stored in the one or more identifiedpillars to produce data file specific encoded data slices, wherein theidentified encoded data slices includes the data file specific encodeddata slices for each of the one or more identified data files.

The method continues at step 208 where the processing module deletes theidentified encoded data slices. The deleting the identified encoded dataslices includes reclaiming memory space of the deleted encoded dataslices and updating pillar mapping of the memory in accordance with thedecreasing of the pillar width parameter and the reclaimed memory space.

FIG. 9A is a schematic block diagram of another embodiment of acomputing system that includes a computing device 220 and a dispersedstorage network (DSN) memory 22. The DSN memory 22 includes one or moreof a secondary magnetic drive memory, a computing device memory, a userdevice memory, and at least one set of DS units. The computing device220 includes a DS module 222 and a local memory 174. The local memory174 may include one or more memory devices, wherein each memory deviceincludes one or more of a flash memory 102, a magnetic drive memory 104,a primary magnetic drive memory, a computing device memory, a local userdevice memory, a solid-state memory, and an optical memory. The DSmodule 222 includes a store data files module 224, a determine pillaradjustment module 226, and an expand pillars module 228.

The store data files module 224, when operable within a computing device220, causes the computing device 220 to store data files 182 utilizing adispersed storage error coding function, wherein a data file of the datafiles is encoded using the dispersed storage error coding function toproduce a plurality of sets of encoded data slices 184, wherein theplurality of sets of encoded data slices is stored in memory, andwherein the dispersed storage error coding function includes a pillarwidth parameter and a decode threshold parameter, where the pillar widthparameter is greater than the decode threshold parameter (e.g., a pillarwidth parameter of 20 and a decode threshold parameter of 10). Thememory includes one or more of the local memory 174 and a DSN memory 22.The store data files module 224, when operable within the computingdevice 220, further causes the computing device 220 to encode asubsequent data file utilizing an increased pillar width parameter 230(e.g., 60), the decode threshold parameter, and the dispersed storageerror coding function to produce a subsequent plurality of sets ofencoded data slices and store the subsequent plurality of sets ofencoded data slices in the memory.

The determine pillars adjustment module 226, when operable within thecomputing device 220, causes the computing device 220 to determinewhether to adjust the pillar width parameter based one or more memoryperformance characteristics 188 (e.g., memory availability and/or memoryreliability). The determine pillar adjustment module 226, when operablewithin the computing device 220, further causes the computing device 220to determine to increase the pillar width parameter by one or more ofdetermining a memory utilization indicator associated with the memory,determining a memory reliability indicator associated with the memory,and when the memory utilization indicator is favorable and the memoryreliability indicator is unfavorable, indicating an increase of thepillar width parameter. The memory utilization indicator includes one ormore of an amount of available memory, an amount of utilized memory,available memory percentage of memory capacity, and utilized memorypercentage of memory capacity. The memory reliability indicator includesone or more of an access latency level of the local memory, a rebuildingfrequency indicator, and a data retrieval reliability level of thememory. For example, the determine pillar adjustment module 226increases the pillar width parameter from 20 to 60 when an amount ofutilized memory is less than a memory threshold and a data retrievalreliability level compares unfavorably to a reliability threshold.

When the pillar width parameter is to be increased, the expand pillarsmodule 228, when operable within the computing device 220, causes thecomputing device 220 to determine a number of additional pillars toproduce the increased pillar width parameter 230, identify one or moreof the data files based on data file criteria (e.g., by a useridentifier, a priority indicator), and for each of the one or more datafiles encode a data file of the one or more data files utilizing theincreased pillar width parameter, the decode threshold parameter, andthe dispersed storage error coding function to produce a plurality ofsubsets of encoded data slices 232 relating to the number of additionalpillars (e.g., retrieve data from a decode threshold number of slices,and use new rows of an extended generator matrix to produce theplurality of subsets of encoded data slices), and store the plurality ofsubsets of encoded data slices 232 in the memory corresponding to theadditional pillars.

The expand pillars module 228, when operable within the computingdevice, further causes the computing device to determine the number ofadditional pillars by one or more of determining a level ofunfavorability of the memory reliability indicator and determining thenumber of additional pillars based on the level of unfavorability. Forexample, the expand pillars module 228 determines 40 additional pillars(e.g., 21-60) when a level of memory reliability is much lower than alow reliability threshold. The expand pillars module 228 furtherfunctions to store the plurality of subsets of encoded data slices 232by updating pillar mapping of the memory in accordance with theincreasing of the pillar width parameter (e.g., wider slice name rangeassigned to memory).

FIG. 9B is a flowchart illustrating an example of expanding datastorage. The method begins at step 240 where a processing module (e.g.,of a computing device) stores data files utilizing a dispersed storageerror coding function, wherein a data file of the data files is encodedusing the dispersed storage error coding function to produce a pluralityof sets of encoded data slices, wherein the plurality of sets of encodeddata slices is stored in memory, and wherein the dispersed storage errorcoding function includes a pillar width parameter and a decode thresholdparameter, where the pillar width parameter is greater than the decodethreshold parameter. The memory includes one or more of a local memoryand a dispersed storage network (DSN) memory. Alternatively, or inaddition to, the processing module encodes a subsequent data fileutilizing an increased pillar width parameter, the decode thresholdparameter, and the dispersed storage error coding function to produce asubsequent plurality of sets of encoded data slices and stores thesubsequent plurality of sets of encoded data slices in the memory.

The method continues at step 242 where the processing module determineswhether to adjust the pillar width parameter based one or more memoryperformance characteristics (e.g., memory availability and/or memoryreliability). The determining to increase the pillar width parameterincludes determining a memory utilization indicator associated with thememory, determining a memory reliability indicator associated with thememory, and when the memory utilization indicator is favorable and thememory reliability indicator is unfavorable, indicating an increase ofthe pillar width parameter.

When the pillar width parameter is to be increased, the method continuesat step 244 where the processing module determines a number ofadditional pillars to produce an increased pillar width parameter. Thedetermining the number of additional pillars includes determining alevel of unfavorability of the memory reliability indicator anddetermining the number of additional pillars based on the level ofunfavorability. The method continues at step 246 where the processingmodule identifies one or more of the data files based on data filecriteria (e.g., based on a user identifier, a priority indicator). Forexample, the processing module identifies 1000 data files that areassociated with a high priority indicator associated with a requirementfor high data retrieval reliability.

For each of the one or more data files, the method continues at step 248where the processing module encodes a data file of the one or more datafiles utilizing the increased pillar width parameter, the decodethreshold parameter, and the dispersed storage error coding function toproduce a plurality of subsets of encoded data slices relating to thenumber of additional pillars (e.g., retrieve data from a decodethreshold number of encoded data slices retrieved from the memory,matrix multiply the data by new rows of an extended generator matrix toproduce the plurality of subsets of encoded data slices). The methodcontinues at step 250 where the processing module stores the pluralityof subsets of encoded data slices in the memory corresponding to theadditional pillars. The storing the plurality of subsets of encoded dataslices includes updating pillar mapping of the memory in accordance withthe increasing of the pillar width parameter (e.g., wider slice namerange assigned to memory).

FIG. 10A is a schematic block diagram of another embodiment of acomputing system that includes a computing device 260, a local areanetwork (LAN) 262, and a wide area network (WAN) 264. The WAN 264includes a dispersed storage network (DSN) memory 22. The DSN memory 22includes one or more of a secondary magnetic drive memory, a computingdevice memory, a user device memory, and at least one set of DS units.The LAN 262 includes a plurality of mobile device memories 266 and aplurality of fixed device memories 268. The fixed device memory 268 issubstantially permanently associated with the LAN 262 whereas the mobiledevice memory 266 may become disassociated with the LAN 262 from time totime. For example, a first mobile device memory 266 includes a smartphone that is utilized in association with the LAN 262 when the firstmobile device 266 is proximally associated with a LAN 262. As anotherexample, a first fixed device memory 268 is associated with a cableset-top box of a home based LAN 262. The mobile device memory 266 andthe fixed device memory 268 may include one or more memory devices,wherein each memory device includes one or more of a flash memory 102, amagnetic drive memory 104, a primary magnetic drive memory, a computingdevice memory, a local device memory, a solid-state memory, and anoptical memory.

The mobile device memory 266 includes mobile device available memory 266when at least some of the one or more memory devices associated with themobile device memory 266 are available for storage access. The fixeddevice memory 268 includes fixed device available memory 268 when atleast some of the one or more memory devices associated with the fixeddevice memory 268 are available for storage access. The computing device260 includes a dispersed storage (DS) module 270 and may include one ormore of the mobile device memory 266 and the fixed device memory 268.The DS module 270 includes an encode module 272, a select LAN widthmodule 274, a select WAN width module 276, a receive request module 278,a request LAN slices module 280, a decode module 282, and a request WANslices module 284.

The encode module 272, when operable within the computing device 260,causes the computing device 260 to encode, in accordance with adispersed storage error coding function, data 286 based on a decodethreshold parameter and a pillar width parameter to produce a set ofencoded data slices 288. The encode module 272 further functions toencode the data 286 by determining the decode threshold parameter basedon a minimum quantity of the fixed device available memory 268 anddetermining the pillar width parameter based on the minimum quantity ofthe fixed device available memory 268 and a minimum quantity of themobile device available memory 266. For example, the encode module 272determines the decode threshold parameter to be 3 when a quantity of thefixed device available memory 268 is 3 fixed devices 268. As anotherexample, the encode module 272 determines the decode threshold parameterto be 10 when a quantity of the fixed device available memory 268 is 15fixed devices 268 and a decode threshold parameter minimum number is 10.As yet another example, the encode module 272 determines the pillarwidth parameter to be 5 when the quantity of the fixed device availablememory 268 is 3 fixed devices 268 and a quantity of the mobile deviceavailable memory 266 is 3. As a still further example, the encode module272 determines the pillar width parameter to be 16 when the quantity ofthe fixed device available memory 268 is 15 fixed devices 268, aquantity of the mobile device available memory 266 is 12, and a pillarwidth parameter minimum number is 16.

The select LAN width module 274, when operable within the computingdevice 260, causes the computing device 260 to select a local areanetwork (LAN) pillar width value of encoded data slices 290 of the setof encoded data slices 288 for storage in LAN available memories (e.g.,available mobile device memories 266 and/or available fixed devicememories 268), wherein the LAN pillar width value is based on the decodethreshold parameter, the pillar width parameter, and quantities of theLAN available memories and wherein the LAN pillar width value is equalto or greater than a value of the decode threshold parameter. The LANavailable memories includes mobile device available memory 266 and fixeddevice available memory 268. The select LAN width module 274 may selectthe LAN pillar width value as less than a value of the pillar widthparameter. For example the select LAN width module 274 selects a LANpillar width value of 12 when the pillar width parameter is 16.

The select WAN width module 276, when operable within the computingdevice 260, causes the computing device 260 to select a wide areanetwork (WAN) pillar width value of encoded data slices 292 of the setof encode data slices 288 for storage in the DSN memory 22 of the widearea network 264, wherein the WAN pillar width value is based on thedecode threshold parameter and the pillar width parameter and whereinthe WAN pillar width value is equal to or greater than the value of thedecode threshold parameter. The select WAN width module 276 may selectthe WAN pillar width value as less than a value of the pillar widthparameter. For example the select WAN width module 276 selects a WANpillar width value of 12 when the pillar width parameter is 16.

The receive request module 278, when operable within the computingdevice 260, causes the computing device 260 to receive a request 294 toretrieve the data 286. The request LAN slices module 280, when operablewithin the computing device 260, causes the computing device 260 todetermine whether the LAN is accessible (e.g., based on a query to oneor more mobile device memories 266 and/or one or more fixed devicememories 268), and when the LAN is accessible, request the LAN pillarwidth value of encoded data slices from the LAN memories (e.g., sendingLAN slices requests 296 to the LAN memories). For example, the requestLAN slices module 280 sends 12 LAN slice requests 296 to the LANmemories when a LAN pillar width value is 12.

The decode module 282, when operable within the computing device 260,causes the computing device 260 to, when at least a decode thresholdparameter of the LAN pillar width value of encoded data slices 290 havebeen received, decode, in accordance with the dispersed storage errorcoding function to produce the data 286. The request WAN slices module284, when operable within the computing device 260, causes the computingdevice 260 to, when the at least the decode threshold parameter of theLAN pillar width value of encoded data slices have not been received,request at least one of the WAN pillar width value of encoded dataslices 292 from the DSN memory 22 (e.g., via at least one WAN slicerequest 298). For example, the request WAN slices module 284 sends threeWAN slice requests 298 to the DSN memory 22 when the decode thresholdparameter is 10 and 7 LAN slices 290 have been received. When the LAN262 is not accessible, the request WAN slices module 284 requests theWAN pillar width value of encoded data slices 292 from the DSN memory22. For example, the request WAN slices module 284 sends 12 WAN slicerequests 298 to the DSN memory 22 when the LAN 262 is not accessible.

FIG. 10B is a flowchart illustrating an example of accessing data. Themethod begins at step 300 where a processing module (e.g., of acomputing device) encodes, in accordance with a dispersed storage errorcoding function, data based on a decode threshold parameter and a pillarwidth parameter to produce a set of encoded data slices. The encodingthe data includes determining the decode threshold parameter based on aminimum quantity of the fixed device available memory and determiningthe pillar width parameter based on the minimum quantity of the fixeddevice available memory and a minimum quantity of the mobile deviceavailable memory.

The method continues at step 302 where the processing module selects alocal area network (LAN) pillar width value of encoded data slices ofthe set of encoded data slices for storage in LAN available memories,wherein the LAN pillar width value is based on the decode thresholdparameter, the pillar width parameter, and quantities of the LANavailable memories and wherein the LAN pillar width value is equal to orgreater than a value of the decode threshold parameter. The LANavailable memories includes mobile device available memory and fixeddevice available memory. The LAN pillar width value may be less than avalue of the pillar width parameter to provide data retrieval capabilitywithout utilizing LAN memories to store all the slices.

The method continues at step 304 where the processing module selects awide area network (WAN) pillar width value of encoded data slices of theset of encode data slices for storage in a dispersed storage network(DSN) memory of a wide area network, wherein the WAN pillar width valueis based on the decode threshold parameter and the pillar widthparameter and wherein the WAN pillar width value is equal to or greaterthan the value of the decode threshold parameter. The WAN pillar widthvalue may be less than a value of the pillar width parameter to providedata retrieval capability without utilizing the DSN memory to store allthe slices.

The method continues at step 306 where the processing module receives arequest to retrieve the data. The method continues at step 308 where theprocessing module determines whether the LAN is accessible. For example,the processing module initiates a query to a memory device associatedwith the LAN. The method branches to step 312 when the processing moduledetermines that the LAN is accessible. The method continues to step 310when the processing module determines that the LAN is not accessible.The method continues at step 310 where the processing module requeststhe WAN pillar width value of encoded data slices from the DSN memorywhen the LAN is not accessible. The method branches to step 316.

The method continues at step 312 where the processing module requeststhe LAN pillar width value of encoded data slices from the LAN memorieswhen the LAN is accessible. When the at least the decode thresholdparameter of the LAN pillar width value of encoded data slices have notbeen received, the method continues at step 314 where the processingmodule requests at least one (e.g., enough to provide a decode thresholdnumber of encoded data slices) of the WAN pillar width value of encodeddata slices from the DSN memory. The method continues at step 316, whenat least a decode threshold parameter of the LAN pillar width value ofencoded data slices have been received, where the processing moduledecodes, in accordance with the dispersed storage error coding functionto produce the data.

FIG. 10C is a schematic block diagram of another embodiment of acomputing system that includes a computing device 320, a local areanetwork (LAN) 262, and a wide area network (WAN) 264. The WAN 264includes a dispersed storage network (DSN) memory 22. The DSN memory 22includes one or more of a secondary magnetic drive memory, a computingdevice memory, a user device memory, and at least one set of DS units.The LAN 262 includes a plurality of mobile device memories 266 and aplurality of fixed device memories 268. For example, a laptop computerincludes a mobile device memory 266. As another example, desktopcomputer includes a fixed device memory 268. The mobile device memory266 and the fixed device memory 268 may include one or more memorydevices, wherein each memory device includes one or more of a flashmemory 102, a magnetic drive memory 104, a primary magnetic drivememory, a computing device memory, a local device memory, a solid-statememory, and an optical memory.

The mobile device memory 266 includes mobile device available memory 266when at least some of the one or more memory devices associated with themobile device memory 266 are available for storage access. The fixeddevice memory 268 includes fixed device available memory 268 when atleast some of the one or more memory devices associated with the fixeddevice memory 268 are available for storage access. The computing device320 includes a dispersed storage (DS) module 322 and may include one ormore of the mobile device memory 266 and the fixed device memory 268.The DS module 322 functions to set up the LAN 262 and WAN 264 andincludes a determine LAN memories module 324, an establish parametersmodule 326, a determine LAN pillar width module 328, and a determine WANpillar width module 330.

The determine LAN memories module 324, when operable within thecomputing device 320, causes the computing device 320 to determine LANavailable memories of the LAN 262 environment. The determine LANmemories module 324 functions to determine the LAN available memories byidentifying one or more mobile device available memories 266 andidentifying one or more fixed device available memories 268. Forexample, the determine LAN memories module 324 sends an availabilityrequest 332 to one or more mobile device memories 266 and one or morefixed device memories 268 and receives availability responses 334 whichidentifies LAN available memories.

The establish parameters module 326, when operable within the computingdevice 320, causes the computing device 320 to establish a decodethreshold parameter 336 and a pillar width parameter 338 of a dispersedstorage error coding function based on quantities of the LAN availablememories. The establish parameters module 326 functions to establish thedecode threshold parameter 336 and the pillar width parameter 338 bydetermining the decode threshold parameter 336 based on a minimumquantity of the fixed device available memory and determining the pillarwidth parameter 338 based on the minimum quantity of the fixed deviceavailable memory and a minimum quantity of the mobile device availablememory. For example, the establish parameters module 326 establishes adecode threshold parameter 336 to be 10 and a pillar width parameter 338to be 16 when a minimum quantity of the fixed device available memory is10, eight mobile device memories 266 are available, and 12 fixed devicememories 268 are available.

The determine LAN pillar width module 328, when operable within thecomputing device 320, causes the computing device 320 to determine a LANpillar width value 340 based on the decode threshold parameter 336, thepillar width parameter 338, and the quantities of the LAN availablememories, wherein the LAN pillar width value 340 is equal to or greaterthan a value of the decode threshold parameter 336. The determine LANpillar width module 328 is further operable to determine the LAN pillarwidth value 340 to be less than a value of the pillar width parameter338. For example, the determine LAN pillar width module 328 determines aLAN pillar width value 340 to be 12 when the decode threshold parameter336 is 10, the pillar width parameter 338 is 16, and there are greaterthan 12 LAN available memories.

The determine WAN pillar width module 330, when operable within thecomputing device 320, causes the computing device 320 to determine a WANpillar width value 342 based on the decode threshold parameter 336 andthe pillar width parameter 338, wherein the WAN pillar width value 342is equal to or greater than the value of the decode threshold parameter336, wherein, for data that is encoded into a set of encoded data slicesin accordance with the dispersed storage error coding function, thedecode threshold parameter 336, and the pillar width parameter 338, aLAN pillar width value 340 of encoded data slices of the set of encodeddata slices are selected for storage in the LAN available memories, anda WAN pillar width value 342 of encoded data slices of the set of encodedata slices for storage in the DSN memory 22 of the WAN 264. Thedetermine WAN pillar width module 330 is further operable to determinethe WAN pillar width value 342 to be less than the value of the pillarwidth parameter 338. For example, the determine WAN pillar width module330 determines a WAN pillar width value 342 to be 11 when the decodethreshold parameter 336 is 10 and the pillar width parameter 338 is 16.

FIG. 10D is a flowchart illustrating an example of setting up adispersed storage system. The method begins at step 350 where aprocessing module (e.g., of a computing device) determines LAN availablememories of a local area network (LAN) environment. The determining LANavailable memories includes identifying one or more mobile deviceavailable memories and identifying one or more fixed device availablememories. The method continues at step 352 where the processing moduleestablishes a decode threshold parameter and a pillar width parameter ofa dispersed storage error coding function based on quantities of the LANavailable memories. The establishing the decode threshold parameter andthe pillar width parameter includes determining the decode thresholdparameter based on a minimum quantity of the fixed device availablememory and determining the pillar width parameter based on the minimumquantity of the fixed device available memory and a minimum quantity ofthe mobile device available memory.

The method continues at step 354 where the processing module determinesa LAN pillar width value based on the decode threshold parameter, thepillar width parameter, and the quantities of the LAN availablememories, wherein the LAN pillar width value is equal to or greater thana value of the decode threshold parameter. Alternatively, the processingmodule determines the LAN pillar width value to be less than a value ofthe pillar width parameter. The method continues at step 356 where theprocessing module determines a WAN pillar width value based on thedecode threshold parameter and the pillar width parameter, wherein theWAN pillar width value is equal to or greater than the value of thedecode threshold parameter, wherein, for data that is encoded into a setof encoded data slices in accordance with the dispersed storage errorcoding function, the decode threshold parameter, and the pillar widthparameter, a LAN pillar width value of encoded data slices of the set ofencoded data slices are selected for storage in the LAN availablememories, and a WAN pillar width value of encoded data slices of the setof encode data slices for storage in a distributed storage network (DSN)memory of the WAN. Alternatively, the processing module determines theWAN pillar width value to be less than the value of the pillar widthparameter.

FIG. 11 is a flowchart illustrating an example of transferring data. Themethod begins with step 360 where a processing module determines whetherto transfer encoded data slices stored in a local Flash memory whendetecting a shutdown. The detecting a shutdown includes or more ofreceiving a shutdown message, detecting a power failure, detecting aprocessing failure, executing a query, receiving a message, receiving acommand, receiving a request, looking up a predetermination, and lookingup a schedule. The determination may be based on one or more of astorage requirement, a storage indicator, a memory type indicator, aslice priority indicator, a data type indicator, a user identifier (ID),a vault ID, a slice volume indicator, an estimated time to transferslices, and an estimated time to power off. For example, the processingmodule determines to transfer the encoded data slices when a slicepriority indicator associated with the encoded data slices comparesfavorably to a slice priority threshold, and the estimated time totransfer slices compares favorably to the estimated time to power off.The method loops at step 360 when the processing module determines notto transfer the encoded data slices. The method continues to step 362when the processing module determines to transfer the encoded dataslices.

The method continues at step 362 where the processing module determinesa group of encoded data slices stored in the local flash memory totransfer. The group of encoded data slices may include at least a decodethreshold number of encoded data slices per set of encoded data slices.The determination may be based on one or more of error coding dispersalstorage function parameters, the storage requirement, the storageindicator, the memory type indicator, the slice priority indicator, thedata type indicator, the user ID, the vault ID, the slice volumeindicator, the estimated time to transfer slices, and the estimated timeto power off. For example, the processing module determines the group ofencoded data slices to include 12 encoded data slices per set of encodeddata slices when the error coding dispersal storage option parametersincludes a read threshold of 12 and a decode threshold of 10.

The method continues at step 364 where the processing module determineswhere to store the group of encoded data slices to produce at least onestorage location. The storage location may include one or more otheruser devices, wherein the one or more other user devices are affiliatedwith a current user device such that each of the other user devices isassociated with a storage indicator indicating a favorable level ofFlash memory capacity sufficient to store the group of encoded dataslices. The determination may be based on one or more of an alternativememory list, a query, a message, a size of the group of encoded dataslices, a predetermination, a lookup, a request, a command, and amessage.

The method continues at step 368 where the processing module transfersthe group of encoded data slices to the at least one storage location.The transferring may include retrieving the group of encoded data slicesand outputting the group of encoded data slices to the lease one storagelocation. The method continues at step 370 where the process moduleoutputs a message indicating that the group of encoded data slices hasbeen transferred. The outputting may include sending the message to oneor more of another user device, a dispersed storage (DS) processingunit, and a DS managing unit. The processing module may receive asubsequent shutdown message in response to sending the message. Next,the processing module completes a final shutdown process when receivinga shutdown message.

FIG. 12A is a flowchart illustrating an example of generating an encodeddata slice storage solicitation message. The method begins with step 372where a processing module determines a utilization level of a localflash memory. The method continues at step 374 where the processingmodule determines whether the utilization level compares favorably to autilization threshold. For example, the processing module determinesthat the utilization level compares favorably to the utilizationthreshold when the utilization level is less than the utilizationthreshold. The method branches to step 376 when the processing moduledetermines that the utilization level compares favorably to theutilization threshold. The method loops back to step 372 when theprocessing module determines that the utilization level does not comparefavorably to the utilization threshold (e.g., no storage capacity toshare).

The method continues at step 376 where the processing module generatesand sends an encoded data slice storage solicitation message to one ormore other user devices. The solicitation message includes one or moreof an available amount of memory indicator, a user device identifier(ID), a performance history indicator, a group ID, a vault ID, and aone-time/on-going indicator (e.g., one-time: transfer now only;on-going: transfer now and for subsequent transfer and storageoperations). The sending includes outputting the data slice storageslice solicitation message to one or more of a random user device, anaffiliated user device, a group of affiliated user devices, one or moreother user devices that previously output a request for stories message,and a list of targets. The method continues step 378 where theprocessing module receives a plurality of encoded data slices from theone or more other user devices. The method continues at step 380 wherethe processing module stores the plurality of encoded data slices in thelocal flash memory. The method may repeat back to step 372.

FIG. 12B is a flowchart illustrating an example of processing an encodeddata slice storage solicitation message that includes similar steps toFIG. 11. The method begins at step 382 where a processing modulereceives an encoded data slice storage solicitation message from anotheruser device. The method continues at step 384 where the processingmodule determines whether to transfer encoded data slices that arestored in a local Flash memory. The determination may be based on one ormore of the storage requirement, a storage indicator, a utilizationlevel indicator, a utilization level threshold, a permissions list, anaffiliation list, information in the solicitation message, apredetermination, a lookup, a message, a request, and a command. Forexample, the processing module determines to transfer encoded dataslices when a user identifier (ID) associated with the solicitationmessage compares favorably to the permissions list and the utilizationlevel indicator compares unfavorably to the utilization level threshold.The method loops back to step 382 when the processing module determinesnot to transfer encoded data slices. The method continues to step 362 ofFIG. 11 when the processing module determines to transfer encoded dataslices.

The method continues with step 362 of FIG. 11 where the processingmodule determines a group of encoded data slices stored in the localFlash memory to transfer. The method continues at step 388 where theprocessing module transfers the group of encoded data slices to theother user device. The transferring includes retrieving the group ofencoded data slices from the local flash memory and outputting the groupof encoded data slices to the other user device.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method comprises: storing data files utilizinga dispersed storage error coding function, wherein a data file of thedata files is encoded using the dispersed storage error coding functionto produce a plurality of sets of encoded data slices, wherein theplurality of sets of encoded data slices is stored in memory, andwherein the dispersed storage error coding function includes a pillarwidth parameter and a decode threshold parameter, where the pillar widthparameter is at least 1.8 times the decode threshold parameter;determining whether to adjust the pillar width parameter based one ormore memory performance characteristics; and when the pillar widthparameter is to be decreased: identifying one or more pillars within thememory to delete to produce one or more identified pillars; identifyingencoded data slices of one or more of the data files stored in the oneor more identified pillars to produce identified encoded data slices;and deleting the identified encoded data slices.
 2. The method of claim1, wherein determining to decrease the pillar width parameter comprises:determining a memory utilization indicator associated with the memory;determining a memory reliability indicator associated with the memory;and when the memory utilization indicator is unfavorable and the memoryreliability indicator is favorable, indicating a decrease of the pillarwidth parameter.
 3. The method of claim 1, wherein the identifying oneor more pillars within the memory to delete comprises: determining anamount of memory space to reclaim based on at least one of: a memoryutilization indicator and a memory reliability indicator; identifyingone or more of the data files based on data file criteria; anddetermining a number of pillars to be deleted based on the amount ofmemory space to reclaim and the identified one or more of the datafiles.
 4. The method of claim 1, wherein the deleting the identifiedencoded data slices comprises: reclaiming memory space of the deletedencoded data slices to produce reclaimed memory space; and updatingpillar mapping of the memory in accordance with the decreasing of thepillar width parameter and the reclaimed memory space.
 5. The method ofclaim 1, wherein the identifying encoded data slices comprises:identifying the one or more of the data files; and for each of the oneor more identified data files: determining which of the encoded dataslices of a respective plurality of sets of encoded data slices arestored in the one or more identified pillars to produce data filespecific encoded data slices, wherein the identified encoded data slicesincludes the data file specific encoded data slices for each of the oneor more identified data files.
 6. The method of claim 1, wherein thememory comprises one or more of: a local memory; and a dispersed storagenetwork (DSN) memory.
 7. The method of claim 1 further comprises:encoding a subsequent data file utilizing the decreasing of the pillarwidth parameter, the decode threshold parameter, and the dispersedstorage error coding function to produce a subsequent plurality of setsof encoded data slices; and storing the subsequent plurality of sets ofencoded data slices in the memory.
 8. A method comprises: storing datafiles utilizing a dispersed storage error coding function, wherein adata file of the data files is encoded using the dispersed storage errorcoding function to produce a plurality of sets of encoded data slices,wherein the plurality of sets of encoded data slices is stored inmemory, and wherein the dispersed storage error coding function includesa pillar width parameter and a decode threshold parameter, where thepillar width parameter is greater than the decode threshold parameter;determining whether to adjust the pillar width parameter based one ormore memory performance characteristics; and when the pillar widthparameter is to be increased: determining a number of additional pillarsto produce an increased pillar width parameter; identifying one or moreof the data files based on data file criteria; and for each of the oneor more data files: encoding a data file of the one or more data filesutilizing the increased pillar width parameter, the decode thresholdparameter, and the dispersed storage error coding function to produce aplurality of subsets of encoded data slices relating to the number ofadditional pillars; and storing the plurality of subsets of encoded dataslices in the memory corresponding to the additional pillars.
 9. Themethod of claim 8 further comprises: the determining to increase thepillar width parameter including: determining a memory utilizationindicator associated with the memory; determining a memory reliabilityindicator associated with the memory; and when the memory utilizationindicator is favorable and the memory reliability indicator isunfavorable, indicating an increase of the pillar width parameter; andthe determining the number of additional pillars including: determininga level of unfavorability of the memory reliability indicator; anddetermining the number of additional pillars based on the level ofunfavorability.
 10. The method of claim 8, wherein the storing theplurality of subsets of encoded data slices comprises: updating pillarmapping of the memory in accordance with the increasing of the pillarwidth parameter.
 11. The method of claim 8, wherein the memory comprisesone or more of: a local memory; and a dispersed storage network (DSN)memory.
 12. The method of claim 8 further comprises: encoding asubsequent data file utilizing the increased pillar width parameter, thedecode threshold parameter, and the dispersed storage error codingfunction to produce a subsequent plurality of sets of encoded dataslices; and storing the subsequent plurality of sets of encoded dataslices in the memory.
 13. A dispersed storage (DS) module comprises: afirst module, when operable within a computing device, causes thecomputing device to: store data files utilizing a dispersed storageerror coding function, wherein a data file of the data files is encodedusing the dispersed storage error coding function to produce a pluralityof sets of encoded data slices, wherein the plurality of sets of encodeddata slices is stored in memory, and wherein the dispersed storage errorcoding function includes a pillar width parameter and a decode thresholdparameter, where the pillar width parameter is at least 1.8 times thedecode threshold parameter; a second module, when operable within thecomputing device, causes the computing device to: determine whether toadjust the pillar width parameter based one or more memory performancecharacteristics; and when the pillar width parameter is to be decreased,a third module, when operable within the computing device, causes thecomputing device to: identify one or more pillars within the memory todelete to produce one or more identified pillars; identify encoded dataslices of one or more of the data files stored in the one or moreidentified pillars to produce identified encoded data slices; and deletethe identified encoded data slices.
 14. The DS module of claim 13,wherein the second module functions to determine to decrease the pillarwidth parameter by: determining a memory utilization indicatorassociated with the memory; determining a memory reliability indicatorassociated with the memory; and when the memory utilization indicator isunfavorable and the memory reliability indicator is favorable,indicating a decrease of the pillar width parameter.
 15. The DS moduleof claim 13, wherein the third module functions to identify the one ormore pillars within the memory to delete by: determining an amount ofmemory space to reclaim based on at least one of: a memory utilizationindicator and a memory reliability indicator; identifying one or more ofthe data files based on data file criteria; and determining a number ofpillars to be deleted based on the amount of memory space to reclaim andthe identified one or more of the data files.
 16. The DS module of claim13, wherein the third module functions to delete the identified encodeddata slices by: reclaiming memory space of the deleted encoded dataslices; and updating pillar mapping of the memory in accordance with thedecreasing of the pillar width parameter and the reclaimed memory space.17. The DS module of claim 13, wherein the third module functions toidentify the encoded data slices by: identifying the one or more of thedata files; and for each of the one or more identified data files:determining which of the encoded data slices of a respective pluralityof sets of encoded data slices are stored in the one or more identifiedpillars to produce data file specific encoded data slices, wherein theidentified encoded data slices includes the data file specific encodeddata slices for each of the one or more identified data files.
 18. TheDS module of claim 13, wherein the memory comprises one or more of: alocal memory; and a dispersed storage network (DSN) memory.
 19. The DSmodule of claim 13 further comprises: the first module, when operablewithin the computing device, further causes the computing device to:encode a subsequent data file utilizing the decreased pillar widthparameter, the decode threshold parameter, and the dispersed storageerror coding function to produce a subsequent plurality of sets ofencoded data slices; and store the subsequent plurality of sets ofencoded data slices in the memory.
 20. A dispersed storage (DS) modulecomprises: a first module, when operable within a computing device,causes the computing device to: store data files utilizing a dispersedstorage error coding function, wherein a data file of the data files isencoded using the dispersed storage error coding function to produce aplurality of sets of encoded data slices, wherein the plurality of setsof encoded data slices is stored in memory, and wherein the dispersedstorage error coding function includes a pillar width parameter and adecode threshold parameter, where the pillar width parameter is greaterthan the decode threshold parameter; a second module, when operablewithin the computing device, causes the computing device to: determinewhether to adjust the pillar width parameter based one or more memoryperformance characteristics; and when the pillar width parameter is tobe increased, a third module, when operable within the computing device,causes the computing device to: determine a number of additional pillarsto produce an increased pillar width parameter; identify one or more ofthe data files based on data file criteria; and for each of the one ormore data files: encode a data file of the one or more data filesutilizing the increased pillar width parameter, the decode thresholdparameter, and the dispersed storage error coding function to produce aplurality of subsets of encoded data slices relating to the number ofadditional pillars; and store the plurality of subsets of encoded dataslices in the memory corresponding to the additional pillars.
 21. The DSmodule of claim 20 further comprises: the second module, when operablewithin the computing device, further causes the computing device todetermine to increase the pillar width parameter by one or more of:determining a memory utilization indicator associated with the memory;determining a memory reliability indicator associated with the memory;and when the memory utilization indicator is favorable and the memoryreliability indicator is unfavorable, indicating an increase of thepillar width parameter; and the third module, when operable within thecomputing device, further causes the computing device to determine thenumber of additional pillars by one or more of: determining a level ofunfavorability of the memory reliability indicator; and determining thenumber of additional pillars based on the level of unfavorability. 22.The DS module of claim 20, wherein the third module further functions tostore the plurality of subsets of encoded data slices by: updatingpillar mapping of the memory in accordance with the increasing of thepillar width parameter.
 23. The DS module of claim 20, wherein thememory comprises one or more of: a local memory; and a dispersed storagenetwork (DSN) memory.
 24. The DS module of claim 20 further comprises:the first module, when operable within the computing device, furthercauses the computing device to: encode a subsequent data file utilizingthe increased pillar width parameter, the decode threshold parameter,and the dispersed storage error coding function to produce a subsequentplurality of sets of encoded data slices; and store the subsequentplurality of sets of encoded data slices in the memory.